Skip to main content
×
Home

Diagnosing Zygosity in Infant Twins: Physical Similarity, Genotyping, and Chorionicity

  • Nadine Forget-Dubois (a1), Daniel Pérusse (a2), Gustavo Turecki (a3), Alain Girard (a4), Jean-Michel Billette (a5), Guy Rouleau (a6), Michel Boivin (a7), Jocelyn Malo (a8) and Richard E. Tremblay (a9)...
Abstract
Abstract

We compared the results of different methods for diagnosing zygosity in a sample of 237 same-sex pairs of twins assessed at 5 and 18 months of age. Despite the twins' very young age and early stage of development, physical similarity was concordant with genotyping in 91.9% of cases at 5 months and 93.8% of cases at 18 months, for a subsample of 123 and 113 pairs, respectively. This concordance rate was obtained following a case-by-case assessment of each pair's physical similarity using a shortened version of the Zygosity Questionnaire for Young Twins (Goldsmith, 1991). Taking into account the chorionicity data available from the twins' medical files, we were able to classify correctly 96% of the pairs, an accuracy rate comparable to previously reported rates obtained with older twins. Chorionicity data is especially useful since we found that monochorionic MZ twins are more difficult than dichorionic MZ twins to diagnose by physical similarity at these young ages. The relative cost-benefit of methods based on reported physical similarity and DNA analysis is discussed in light of these results.

    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Diagnosing Zygosity in Infant Twins: Physical Similarity, Genotyping, and Chorionicity
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      Diagnosing Zygosity in Infant Twins: Physical Similarity, Genotyping, and Chorionicity
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      Diagnosing Zygosity in Infant Twins: Physical Similarity, Genotyping, and Chorionicity
      Available formats
      ×
Copyright
Corresponding author
*Address for correspondence: Daniel Pérusse, Research Unit on Children's Psychosocial Maladjustment-University of Montreal, Ste-Justine Hospital Research Center, Bio-psychosocial Unit, Block 5, floor A, 3175, Chemin de la Côte Ste-Catherine, Montreal, Canada, H3T 1C5.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Twin Research and Human Genetics
  • ISSN: 1832-4274
  • EISSN: 1839-2628
  • URL: /core/journals/twin-research-and-human-genetics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 87 *
Loading metrics...

Abstract views

Total abstract views: 132 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 21st November 2017. This data will be updated every 24 hours.